docs/changes/newsfragments/132.change

@@ -0,0 +1 @@
+Expose ``types`` parameter for :class:`.DataladAOMICID1000`, :class:`.DataladAOMICPIOP1`, :class:`.DataladAOMICPIOP2` and :class:`.JuselessUCLA` by `Synchon Mandal`_

docs/changes/newsfragments/132.enh

@@ -0,0 +1 @@
+Change validation of ``types`` against ``patterns`` to allow a subset of ``patterns``'s types to be used for ``DataGrabber`` data fetch by `Synchon Mandal`_

junifer/configs/juseless/datagrabbers/tests/test_ucla.py

@@ -6,20 +6,17 @@
 # License: AGPL
 
 import socket
-from typing import Optional
+from typing import List, Optional, Union
 
 import pytest
 
 from junifer.configs.juseless.datagrabbers import JuselessUCLA
-from junifer.utils.logging import configure_logging
 
 
 # Check if the test is running on juseless
 if socket.gethostname() != "juseless":
     pytest.skip("These tests are only for juseless", allow_module_level=True)
 
-configure_logging(level="DEBUG")
-
 
 def test_JuselessUCLA() -> None:
     """Test JuselessUCLA."""
@@ -42,6 +39,57 @@ def test_JuselessUCLA() -> None:
             assert out[t]["path"].exists()
 
 
+@pytest.mark.parametrize(
+    "types",
+    [
+        "BOLD",
+        "BOLD_confounds",
+        "T1w",
+        "probseg_CSF",
+        "probseg_GM",
+        "probseg_WM",
+        ["BOLD", "BOLD_confounds"],
+        ["T1w", "probseg_CSF"],
+        ["probseg_GM", "probseg_WM"],
+        ["BOLD", "T1w"],
+    ],
+)
+def test_JuselessUCLA_partial_data_access(
+    types: Union[str, List[str]],
+) -> None:
+    """Test JuselessUCLA DataGrabber partial data access.
+
+    Parameters
+    ----------
+    types : str or list of str
+        The parametrized types.
+
+    """
+    dg = JuselessUCLA(types=types)
+
+    with dg:
+        # Get all elements
+        all_elements = dg.get_elements()
+        # Get test element
+        test_element = all_elements[0]
+        # Get test element data
+        out = dg[test_element]
+        # Assert data type
+        if isinstance(types, list):
+            for type_ in types:
+                assert type_ in out
+        else:
+            assert types in out
+
+
+def test_JuselessUCLA_incorrect_data_type() -> None:
+    """Test JuselessUCLA DataGrabber incorrect data type."""
+    with pytest.raises(
+        ValueError, match="`patterns` must contain all `types`"
+    ):
+        _ = JuselessUCLA(types="Eunomia")
+
+
 @pytest.mark.parametrize(
     "tasks",
     [None, "rest", ["rest", "stopsignal"]],

junifer/configs/juseless/datagrabbers/ucla.py

@@ -20,9 +20,13 @@ class JuselessUCLA(PatternDataGrabber):
 
     Parameters
     ----------
-    datadir : str or pathlib.Path, optional
+    datadir : str or Path, optional
-        The directory where the dataset is stored
+        The directory where the dataset is stored.
         (default "/data/project/psychosis_thalamus/data/fmriprep").
+    types: {"BOLD", "BOLD_confounds", "T1w", "probseg_CSF", "probseg_GM", \
+           "probseg_WM"} or a list of the options, optional
+        UCLA data types. If None, all available data types are selected.
+        (default None).
     tasks : {"rest", "bart", "bht", "pamenc", "pamret", \
             "scap", "taskswitch", "stopsignal"} or \
             list of the options or None, optional
@@ -36,20 +40,10 @@ class JuselessUCLA(PatternDataGrabber):
         datadir: Union[
             str, Path
         ] = "/data/project/psychosis_thalamus/data/fmriprep",
+        types: Union[str, List[str], None] = None,
         tasks: Union[str, List[str], None] = None,
     ) -> None:
-        types = [
+        # Declare all tasks
-            "BOLD",
-            "BOLD_confounds",
-            "T1w",
-            "probseg_CSF",
-            "probseg_GM",
-            "probseg_WM",
-        ]
-
-        if isinstance(tasks, str):
-            tasks = [tasks]
-
         all_tasks = [
             "rest",
             "bart",
@@ -60,18 +54,21 @@ class JuselessUCLA(PatternDataGrabber):
             "taskswitch",
             "stopsignal",
         ]
-
+        # Set default tasks
         if tasks is None:
             tasks = all_tasks
         else:
+            # Convert single task into list
+            if isinstance(tasks, str):
+                tasks = [tasks]
+            # Verify valid tasks
             for t in tasks:
                 if t not in all_tasks:
                     raise_error(
                         f"{t} is not a valid task in the UCLA dataset!"
                     )
-
         self.tasks = tasks
-
+        # The patterns
         patterns = {
             "BOLD": (
                 "sub-{subject}/func/sub-{subject}_task-{task}_bold_space-"
@@ -98,12 +95,18 @@ class JuselessUCLA(PatternDataGrabber):
                 "-MNI152NLin2009cAsym_class-WM_probtissue.nii.gz"
             ),
         }
-
+        # Set default types
+        if types is None:
+            types = list(patterns.keys())
+        # Convert single type into list
+        else:
+            if not isinstance(types, list):
+                types = [types]
+        # The replacements
+        replacements = ["subject", "task"]
         # the commented out uri leads to new open neuro dataset which does
         # NOT have preprocessed data
         # uri = "https://github.com/OpenNeuroDatasets/ds000030.git"
-
-        replacements = ["subject", "task"]
         super().__init__(
             types=types,
             datadir=datadir,

junifer/datagrabber/aomic/id1000.py

@@ -4,10 +4,11 @@
 #          Vera Komeyer <v.komeyer@fz-juelich.de>
 #          Xuan Li <xu.li@fz-juelich.de>
 #          Leonard Sasse <l.sasse@fz-juelich.de>
+#          Synchon Mandal <s.mandal@fz-juelich.de>
 # License: AGPL
 
 from pathlib import Path
-from typing import Dict, Union
+from typing import Dict, List, Union
 
 from ...api.decorators import register_datagrabber
 from ..pattern_datalad import PatternDataladDataGrabber
@@ -23,25 +24,18 @@ class DataladAOMICID1000(PatternDataladDataGrabber):
         The directory where the datalad dataset will be cloned. If None,
         the datalad dataset will be cloned into a temporary directory
         (default None).
+    types: {"BOLD", "BOLD_confounds", "T1w", "probseg_CSF", "probseg_GM", \
+           "probseg_WM", "DWI"} or a list of the options, optional
+        AOMIC data types. If None, all available data types are selected.
+        (default None).
 
     """
 
     def __init__(
         self,
         datadir: Union[str, Path, None] = None,
+        types: Union[str, List[str], None] = None,
     ) -> None:
-        # The types of data
-        types = [
-            "BOLD",
-            "BOLD_confounds",
-            "BOLD_mask",
-            "T1w",
-            "T1w_mask",
-            "probseg_CSF",
-            "probseg_GM",
-            "probseg_WM",
-            "DWI",
-        ]
         # The patterns
         patterns = {
             "BOLD": (
@@ -90,6 +84,13 @@ class DataladAOMICID1000(PatternDataladDataGrabber):
                 "sub-{subject}_desc-preproc_dwi.nii.gz"
             ),
         }
+        # Set default types
+        if types is None:
+            types = list(patterns.keys())
+        # Convert single type into list
+        else:
+            if not isinstance(types, list):
+                types = [types]
         # The replacements
         replacements = ["subject"]
         uri = "https://github.com/OpenNeuroDatasets/ds003097.git"
@@ -118,6 +119,8 @@ class DataladAOMICID1000(PatternDataladDataGrabber):
 
         """
         out = super().get_item(subject=subject)
-        out["BOLD"]["mask_item"] = "BOLD_mask"
+        if out.get("BOLD"):
-        out["T1w"]["mask_item"] = "T1w_mask"
+            out["BOLD"]["mask_item"] = "BOLD_mask"
+        if out.get("T1w"):
+            out["T1w"]["mask_item"] = "T1w_mask"
         return out

junifer/datagrabber/aomic/piop1.py

@@ -4,6 +4,7 @@
 #          Vera Komeyer <v.komeyer@fz-juelich.de>
 #          Xuan Li <xu.li@fz-juelich.de>
 #          Leonard Sasse <l.sasse@fz-juelich.de>
+#          Synchon Mandal <s.mandal@fz-juelich.de>
 # License: AGPL
 
 from itertools import product
@@ -25,6 +26,10 @@ class DataladAOMICPIOP1(PatternDataladDataGrabber):
         The directory where the datalad dataset will be cloned. If None,
         the datalad dataset will be cloned into a temporary directory
         (default None).
+    types: {"BOLD", "BOLD_confounds", "T1w", "probseg_CSF", "probseg_GM", \
+           "probseg_WM", "DWI"} or a list of the options, optional
+        AOMIC data types. If None, all available data types are selected.
+        (default None).
     tasks : {"restingstate", "anticipation", "emomatching", "faces", \
             "gstroop", "workingmemory"} or list of the options, optional
         AOMIC PIOP1 task sessions. If None, all available task sessions are
@@ -35,24 +40,10 @@ class DataladAOMICPIOP1(PatternDataladDataGrabber):
     def __init__(
         self,
         datadir: Union[str, Path, None] = None,
+        types: Union[str, List[str], None] = None,
         tasks: Union[str, List[str], None] = None,
     ) -> None:
-        # The types of data
+        # Declare all tasks
-        types = [
-            "BOLD",
-            "BOLD_confounds",
-            "BOLD_mask",
-            "T1w",
-            "T1w_mask",
-            "probseg_CSF",
-            "probseg_GM",
-            "probseg_WM",
-            "DWI",
-        ]
-
-        if isinstance(tasks, str):
-            tasks = [tasks]
-
         all_tasks = [
             "restingstate",
             "anticipation",
@@ -61,19 +52,22 @@ class DataladAOMICPIOP1(PatternDataladDataGrabber):
             "gstroop",
             "workingmemory",
         ]
-
+        # Set default tasks
         if tasks is None:
             tasks = all_tasks
         else:
+            # Convert single task into list
+            if isinstance(tasks, str):
+                tasks = [tasks]
+            # Verify valid tasks
             for t in tasks:
                 if t not in all_tasks:
                     raise_error(
                         f"{t} is not a valid task in the AOMIC PIOP1"
                         " dataset!"
                     )
-
         self.tasks = tasks
-
+        # The patterns
         patterns = {
             "BOLD": (
                 "derivatives/fmriprep/sub-{subject}/func/"
@@ -120,8 +114,16 @@ class DataladAOMICPIOP1(PatternDataladDataGrabber):
                 "sub-{subject}_desc-preproc_dwi.nii.gz"
             ),
         }
-        uri = "https://github.com/OpenNeuroDatasets/ds002785"
+        # Set default types
+        if types is None:
+            types = list(patterns.keys())
+        # Convert single type into list
+        else:
+            if not isinstance(types, list):
+                types = [types]
+        # The replacements
         replacements = ["subject", "task"]
+        uri = "https://github.com/OpenNeuroDatasets/ds002785"
         super().__init__(
             types=types,
             datadir=datadir,
@@ -162,8 +164,10 @@ class DataladAOMICPIOP1(PatternDataladDataGrabber):
         new_task = f"{task}_acq-{acq}"
 
         out = super().get_item(subject=subject, task=new_task)
-        out["BOLD"]["mask_item"] = "BOLD_mask"
+        if out.get("BOLD"):
-        out["T1w"]["mask_item"] = "T1w_mask"
+            out["BOLD"]["mask_item"] = "BOLD_mask"
+        if out.get("T1w"):
+            out["T1w"]["mask_item"] = "T1w_mask"
         return out
 
     def get_elements(self) -> List:

junifer/datagrabber/aomic/piop2.py

@@ -4,8 +4,10 @@
 #          Vera Komeyer <v.komeyer@fz-juelich.de>
 #          Xuan Li <xu.li@fz-juelich.de>
 #          Leonard Sasse <l.sasse@fz-juelich.de>
+#          Synchon Mandal <s.mandal@fz-juelich.de>
 # License: AGPL
 
+from itertools import product
 from pathlib import Path
 from typing import Dict, List, Union
 
@@ -24,7 +26,11 @@ class DataladAOMICPIOP2(PatternDataladDataGrabber):
         The directory where the datalad dataset will be cloned. If None,
         the datalad dataset will be cloned into a temporary directory
         (default None).
-    tasks : {"restingstate", "stopsignal", "emomatching", "workingmemory"} \
+    types: {"BOLD", "BOLD_confounds", "T1w", "probseg_CSF", "probseg_GM", \
+           "probseg_WM", "DWI"} or a list of the options, optional
+        AOMIC data types. If None, all available data types are selected.
+        (default None).
+    tasks : {"restingstate", "stopsignal", "workingmemory"} \
             or list of the options, optional
         AOMIC PIOP2 task sessions. If None, all available task sessions are
         selected (default None).
@@ -34,58 +40,46 @@ class DataladAOMICPIOP2(PatternDataladDataGrabber):
     def __init__(
         self,
         datadir: Union[str, Path, None] = None,
+        types: Union[str, List[str], None] = None,
         tasks: Union[str, List[str], None] = None,
     ) -> None:
-        # The types of data
+        # Declare all tasks
-        types = [
-            "BOLD",
-            "BOLD_confounds",
-            "BOLD_mask",
-            "T1w",
-            "T1w_mask",
-            "probseg_CSF",
-            "probseg_GM",
-            "probseg_WM",
-            "DWI",
-        ]
-
-        if isinstance(tasks, str):
-            tasks = [tasks]
-
         all_tasks = [
             "restingstate",
-            "emomatching",
-            "workingmemory",
             "stopsignal",
+            "workingmemory",
         ]
-
+        # Set default tasks
         if tasks is None:
             tasks = all_tasks
         else:
+            # Convert single task into list
+            if isinstance(tasks, str):
+                tasks = [tasks]
+            # Verify valid tasks
             for t in tasks:
                 if t not in all_tasks:
                     raise_error(
                         f"{t} is not a valid task in the AOMIC PIOP2"
                         " dataset!"
                     )
-
         self.tasks = tasks
-
+        # The patterns
         patterns = {
             "BOLD": (
                 "derivatives/fmriprep/sub-{subject}/func/"
-                "sub-{subject}_task-{task}_acq-seq_"
+                "sub-{subject}_task-{task}_"
                 "space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz"
             ),
             "BOLD_confounds": (
                 "derivatives/fmriprep/sub-{subject}/func/"
-                "sub-{subject}_task-{task}_acq-seq_"
+                "sub-{subject}_task-{task}_"
                 "desc-confounds_regressors.tsv"
             ),
             "BOLD_mask": (
                 "derivatives/fmriprep/sub-{subject}/func/"
-                "sub-{subject}_task-{task}_acq-seq_space"
+                "sub-{subject}_task-{task}_"
-                "-MNI152NLin2009cAsym_desc-brain_mask.nii.gz"
+                "space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz"
             ),
             "T1w": (
                 "derivatives/fmriprep/sub-{subject}/anat/"
@@ -117,8 +111,16 @@ class DataladAOMICPIOP2(PatternDataladDataGrabber):
                 "sub-{subject}_desc-preproc_dwi.nii.gz"
             ),
         }
-        uri = "https://github.com/OpenNeuroDatasets/ds002790"
+        # Set default types
+        if types is None:
+            types = list(patterns.keys())
+        # Convert single type into list
+        else:
+            if not isinstance(types, list):
+                types = [types]
+        # The replacements
         replacements = ["subject", "task"]
+        uri = "https://github.com/OpenNeuroDatasets/ds002790"
         super().__init__(
             types=types,
             datadir=datadir,
@@ -138,8 +140,11 @@ class DataladAOMICPIOP2(PatternDataladDataGrabber):
             imposing constraints based on specified tasks.
 
         """
-        all_elements = super().get_elements()
+        subjects = [f"{x:04d}" for x in range(1, 227)]
-        return [x for x in all_elements if x[1] in self.tasks]
+        elems = []
+        for subject, task in product(subjects, self.tasks):
+            elems.append((subject, task))
+        return elems
 
     def get_item(self, subject: str, task: str) -> Dict:
         """Index one element in the dataset.
@@ -148,9 +153,8 @@ class DataladAOMICPIOP2(PatternDataladDataGrabber):
         ----------
         subject : str
             The subject ID.
-        task : str
+        task : {"restingstate", "stopsignal", "workingmemory"}
-            The task to get. Possible values are:
+            The task to get.
-            {"restingstate", "stopsignal", "emomatching", "workingmemory"}
 
         Returns
         -------
@@ -159,7 +163,9 @@ class DataladAOMICPIOP2(PatternDataladDataGrabber):
             specified element.
 
         """
-        out = super().get_item(subject=subject, task=task)
+        out = super().get_item(subject=subject, task=f"{task}_acq-seq")
-        out["BOLD"]["mask_item"] = "BOLD_mask"
+        if out.get("BOLD"):
-        out["T1w"]["mask_item"] = "T1w_mask"
+            out["BOLD"]["mask_item"] = "BOLD_mask"
+        if out.get("T1w"):
+            out["T1w"]["mask_item"] = "T1w_mask"
         return out

junifer/datagrabber/aomic/tests/test_id1000.py

@@ -4,22 +4,24 @@
 #          Vera Komeyer <v.komeyer@fz-juelich.de>
 #          Xuan Li <xu.li@fz-juelich.de>
 #          Leonard Sasse <l.sasse@fz-juelich.de>
+#          Synchon Mandal <s.mandal@fz-juelich.de>
 # License: AGPL
 
-from junifer.datagrabber import DataladAOMICID1000
+from typing import List, Union
-from junifer.utils import configure_logging
+
+import pytest
+
+from junifer.datagrabber.aomic.id1000 import DataladAOMICID1000
+
+
+URI = "https://gin.g-node.org/juaml/datalad-example-aomic1000"
 
 
 def test_DataladAOMICID1000() -> None:
     """Test DataladAOMICID1000 DataGrabber."""
-
-    uri_ID1000 = "https://gin.g-node.org/juaml/datalad-example-aomic1000"
-    configure_logging(level="DEBUG")
-
     dg = DataladAOMICID1000()
-
+    # Set URI to Gin
-    # change uri here to use fake data instead of real dataset
+    dg.uri = URI
-    dg.uri = uri_ID1000
 
     with dg:
         all_elements = dg.get_elements()
@@ -122,3 +124,57 @@ def test_DataladAOMICID1000() -> None:
         assert "element" in meta
         assert "subject" in meta["element"]
         assert test_element == meta["element"]["subject"]
+
+
+@pytest.mark.parametrize(
+    "types",
+    [
+        "BOLD",
+        "BOLD_confounds",
+        "T1w",
+        "probseg_CSF",
+        "probseg_GM",
+        "probseg_WM",
+        "DWI",
+        ["BOLD", "BOLD_confounds"],
+        ["T1w", "probseg_CSF"],
+        ["probseg_GM", "probseg_WM"],
+        ["DWI", "BOLD"],
+    ],
+)
+def test_DataladAOMICID1000_partial_data_access(
+    types: Union[str, List[str]],
+) -> None:
+    """Test DataladAOMICID1000 DataGrabber partial data access.
+
+    Parameters
+    ----------
+    types : str or list of str
+        The parametrized types.
+
+    """
+    dg = DataladAOMICID1000(types=types)
+    # Set URI to Gin
+    dg.uri = URI
+
+    with dg:
+        # Get all elements
+        all_elements = dg.get_elements()
+        # Get test element
+        test_element = all_elements[0]
+        # Get test element data
+        out = dg[test_element]
+        # Assert data type
+        if isinstance(types, list):
+            for type_ in types:
+                assert type_ in out
+        else:
+            assert types in out
+
+
+def test_DataladAOMICID1000_incorrect_data_type() -> None:
+    """Test DataladAOMICID1000 DataGrabber incorrect data type."""
+    with pytest.raises(
+        ValueError, match="`patterns` must contain all `types`"
+    ):
+        _ = DataladAOMICID1000(types="Scooby-Doo")

junifer/datagrabber/aomic/tests/test_piop1.py

@@ -4,142 +4,201 @@
 #          Vera Komeyer <v.komeyer@fz-juelich.de>
 #          Xuan Li <xu.li@fz-juelich.de>
 #          Leonard Sasse <l.sasse@fz-juelich.de>
+#          Synchon Mandal <s.mandal@fz-juelich.de>
 # License: AGPL
 
+from typing import List, Optional, Union
+
 import pytest
 
 from junifer.datagrabber import DataladAOMICPIOP1
-from junifer.utils import configure_logging
 
 
-def test_DataladAOMICPIOP1() -> None:
+URI = "https://gin.g-node.org/juaml/datalad-example-aomicpiop1"
-    """Test DataladAOMICPIOP1 DataGrabber."""
-    configure_logging(level="DEBUG")
 
-    uri_PIOP1 = "https://gin.g-node.org/juaml/datalad-example-aomicpiop1"
-    task_params = [None, "restingstate"]
 
-    for task_param in task_params:
+@pytest.mark.parametrize(
-        dg = DataladAOMICPIOP1(tasks=task_param)
+    "tasks",
+    [None, "restingstate"],
+)
+def test_DataladAOMICPIOP1(tasks: Optional[str]) -> None:
+    """Test DataladAOMICPIOP1 DataGrabber.
 
-        # change uri here to use fake data instead of real dataset
+    Parameters
-        dg.uri = uri_PIOP1
+    ----------
+    tasks : str or None
+        The parametrized task values.
 
-        with dg:
+    """
-            all_elements = dg.get_elements()
+    dg = DataladAOMICPIOP1(tasks=tasks)
-            test_element = all_elements[0]
+    # Set URI to Gin
-            sub, task = test_element
+    dg.uri = URI
 
-            out = dg[test_element]
+    with dg:
+        all_elements = dg.get_elements()
+        test_element = all_elements[0]
+        sub, task = test_element
 
-            # asserts type "BOLD"
+        out = dg[test_element]
-            assert "BOLD" in out
 
-            # depending on task 'acquisition is different'
+        # asserts type "BOLD"
-            task_acqs = {
+        assert "BOLD" in out
-                "anticipation": "seq",
-                "emomatching": "seq",
-                "faces": "mb3",
-                "gstroop": "seq",
-                "restingstate": "mb3",
-                "workingmemory": "seq",
-            }
-            acq = task_acqs[task]
-            new_task = f"{task}_acq-{acq}"
-            assert (
-                out["BOLD"]["path"].name == f"sub-{sub}_task-{new_task}_"
-                "space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz"
-            )
 
-            assert out["BOLD"]["path"].exists()
+        # depending on task 'acquisition is different'
-            assert out["BOLD"]["path"].is_file()
+        task_acqs = {
+            "anticipation": "seq",
+            "emomatching": "seq",
+            "faces": "mb3",
+            "gstroop": "seq",
+            "restingstate": "mb3",
+            "workingmemory": "seq",
+        }
+        acq = task_acqs[task]
+        new_task = f"{task}_acq-{acq}"
+        assert (
+            out["BOLD"]["path"].name == f"sub-{sub}_task-{new_task}_"
+            "space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz"
+        )
 
-            # asserts type "BOLD_confounds"
+        assert out["BOLD"]["path"].exists()
-            assert "BOLD_confounds" in out
+        assert out["BOLD"]["path"].is_file()
 
-            assert (
+        # asserts type "BOLD_confounds"
-                out["BOLD_confounds"]["path"].name
+        assert "BOLD_confounds" in out
-                == f"sub-{sub}_task-{new_task}_"
-                "desc-confounds_regressors.tsv"
-            )
 
-            assert out["BOLD_confounds"]["path"].exists()
+        assert (
-            assert out["BOLD_confounds"]["path"].is_file()
+            out["BOLD_confounds"]["path"].name == f"sub-{sub}_task-{new_task}_"
+            "desc-confounds_regressors.tsv"
+        )
 
-            # assert BOLD_mask
+        assert out["BOLD_confounds"]["path"].exists()
-            assert out["BOLD_mask"]["path"].exists()
+        assert out["BOLD_confounds"]["path"].is_file()
 
-            # asserts type "T1w"
+        # assert BOLD_mask
-            assert "T1w" in out
+        assert out["BOLD_mask"]["path"].exists()
 
-            assert (
+        # asserts type "T1w"
-                out["T1w"]["path"].name
+        assert "T1w" in out
-                == f"sub-{sub}_space-MNI152NLin2009cAsym_"
-                "desc-preproc_T1w.nii.gz"
-            )
 
-            assert out["T1w"]["path"].exists()
+        assert (
-            assert out["T1w"]["path"].is_file()
+            out["T1w"]["path"].name == f"sub-{sub}_space-MNI152NLin2009cAsym_"
+            "desc-preproc_T1w.nii.gz"
+        )
 
-            # asserts T1w_mask
+        assert out["T1w"]["path"].exists()
-            assert out["T1w_mask"]["path"].exists()
+        assert out["T1w"]["path"].is_file()
 
-            # asserts type "probseg_CSF"
+        # asserts T1w_mask
-            assert "probseg_CSF" in out
+        assert out["T1w_mask"]["path"].exists()
 
-            assert (
+        # asserts type "probseg_CSF"
-                out["probseg_CSF"]["path"].name
+        assert "probseg_CSF" in out
-                == f"sub-{sub}_space-MNI152NLin2009cAsym_label-"
-                "CSF_probseg.nii.gz"
-            )
 
-            assert out["probseg_CSF"]["path"].exists()
+        assert (
-            assert out["probseg_CSF"]["path"].is_file()
+            out["probseg_CSF"]["path"].name
+            == f"sub-{sub}_space-MNI152NLin2009cAsym_label-"
+            "CSF_probseg.nii.gz"
+        )
 
-            # asserts type "probseg_GM"
+        assert out["probseg_CSF"]["path"].exists()
-            assert "probseg_GM" in out
+        assert out["probseg_CSF"]["path"].is_file()
 
-            assert (
+        # asserts type "probseg_GM"
-                out["probseg_GM"]["path"].name
+        assert "probseg_GM" in out
-                == f"sub-{sub}_space-MNI152NLin2009cAsym_label-"
-                "GM_probseg.nii.gz"
-            )
 
-            assert out["probseg_GM"]["path"].exists()
+        assert (
-            assert out["probseg_GM"]["path"].is_file()
+            out["probseg_GM"]["path"].name
+            == f"sub-{sub}_space-MNI152NLin2009cAsym_label-"
+            "GM_probseg.nii.gz"
+        )
 
-            # asserts type "probseg_WM"
+        assert out["probseg_GM"]["path"].exists()
-            assert "probseg_WM" in out
+        assert out["probseg_GM"]["path"].is_file()
 
-            assert (
+        # asserts type "probseg_WM"
-                out["probseg_WM"]["path"].name
+        assert "probseg_WM" in out
-                == f"sub-{sub}_space-MNI152NLin2009cAsym_label-"
-                "WM_probseg.nii.gz"
-            )
 
-            assert out["probseg_WM"]["path"].exists()
+        assert (
-            assert out["probseg_WM"]["path"].is_file()
+            out["probseg_WM"]["path"].name
+            == f"sub-{sub}_space-MNI152NLin2009cAsym_label-"
+            "WM_probseg.nii.gz"
+        )
 
-            # asserts type "DWI"
+        assert out["probseg_WM"]["path"].exists()
-            assert "DWI" in out
+        assert out["probseg_WM"]["path"].is_file()
 
-            assert (
+        # asserts type "DWI"
-                out["DWI"]["path"].name == f"sub-{sub}_desc-preproc_dwi.nii.gz"
+        assert "DWI" in out
-            )
 
-            assert out["DWI"]["path"].exists()
+        assert out["DWI"]["path"].name == f"sub-{sub}_desc-preproc_dwi.nii.gz"
-            assert out["DWI"]["path"].is_file()
 
-            # asserts meta
+        assert out["DWI"]["path"].exists()
-            assert "meta" in out["BOLD"]
+        assert out["DWI"]["path"].is_file()
-            meta = out["BOLD"]["meta"]
+
-            assert "element" in meta
+        # asserts meta
-            assert "subject" in meta["element"]
+        assert "meta" in out["BOLD"]
-            assert sub == meta["element"]["subject"]
+        meta = out["BOLD"]["meta"]
+        assert "element" in meta
+        assert "subject" in meta["element"]
+        assert sub == meta["element"]["subject"]
+
+
+@pytest.mark.parametrize(
+    "types",
+    [
+        "BOLD",
+        "BOLD_confounds",
+        "T1w",
+        "probseg_CSF",
+        "probseg_GM",
+        "probseg_WM",
+        "DWI",
+        ["BOLD", "BOLD_confounds"],
+        ["T1w", "probseg_CSF"],
+        ["probseg_GM", "probseg_WM"],
+        ["DWI", "BOLD"],
+    ],
+)
+def test_DataladAOMICPIOP1_partial_data_access(
+    types: Union[str, List[str]],
+) -> None:
+    """Test DataladAOMICPIOP1 DataGrabber partial data access.
+
+    Parameters
+    ----------
+    types : str or list of str
+        The parametrized types.
+
+    """
+    dg = DataladAOMICPIOP1(types=types)
+    # Set URI to Gin
+    dg.uri = URI
+
+    with dg:
+        # Get all elements
+        all_elements = dg.get_elements()
+        # Get test element
+        test_element = all_elements[0]
+        # Get test element data
+        out = dg[test_element]
+        # Assert data type
+        if isinstance(types, list):
+            for type_ in types:
+                assert type_ in out
+        else:
+            assert types in out
+
+
+def test_DataladAOMICPIOP1_incorrect_data_type() -> None:
+    """Test DataladAOMICPIOP1 DataGrabber incorrect data type."""
+    with pytest.raises(
+        ValueError, match="`patterns` must contain all `types`"
+    ):
+        _ = DataladAOMICPIOP1(types="Ceres")
 
 
 def test_DataladAOMICPIOP1_invalid_tasks():
-    """Test whether invalid task fails."""
+    """Test DataladAOMICIDPIOP1 DataGrabber invalid tasks."""
     with pytest.raises(
         ValueError,
         match=(

junifer/datagrabber/aomic/tests/test_piop2.py

@@ -4,136 +4,195 @@
 #          Vera Komeyer <v.komeyer@fz-juelich.de>
 #          Xuan Li <xu.li@fz-juelich.de>
 #          Leonard Sasse <l.sasse@fz-juelich.de>
+#          Synchon Mandal <s.mandal@fz-juelich.de>
 # License: AGPL
 
+from typing import List, Optional, Union
+
 import pytest
 
 from junifer.datagrabber import DataladAOMICPIOP2
-from junifer.utils import configure_logging
 
 
-def test_DataladAOMICPIOP2() -> None:
+URI = "https://gin.g-node.org/juaml/datalad-example-aomicpiop2"
-    """Test DataladAOMICPIOP2 DataGrabber."""
-    configure_logging(level="DEBUG")
 
-    uri_PIOP2 = "https://gin.g-node.org/juaml/datalad-example-aomicpiop2"
-    task_params = [None, "restingstate"]
 
-    for task_param in task_params:
+@pytest.mark.parametrize(
-        dg = DataladAOMICPIOP2(tasks=task_param)
+    "tasks",
+    [None, "restingstate"],
+)
+def test_DataladAOMICPIOP2(tasks: Optional[str]) -> None:
+    """Test DataladAOMICPIOP2 DataGrabber.
 
-        # change uri here to use fake data instead of real dataset
+    Parameters
-        dg.uri = uri_PIOP2
+    ----------
+    tasks : str or None
+        The parametrized task values.
 
-        with dg:
+    """
-            all_elements = dg.get_elements()
+    dg = DataladAOMICPIOP2(tasks=tasks)
+    # Set URI to Gin
+    dg.uri = URI
 
-            if task_param == "restingstate":
+    with dg:
-                for el in all_elements:
+        all_elements = dg.get_elements()
-                    assert el[1] == "restingstate"
 
-            test_element = all_elements[0]
+        if tasks == "restingstate":
-            sub, task = test_element
+            for el in all_elements:
-            out = dg[test_element]
+                assert el[1] == "restingstate"
 
-            # asserts type "BOLD"
+        test_element = all_elements[0]
-            assert "BOLD" in out
+        sub, task = test_element
+        out = dg[test_element]
 
-            new_task = f"{task}_acq-seq"
+        # asserts type "BOLD"
-            assert (
+        assert "BOLD" in out
-                out["BOLD"]["path"].name == f"sub-{sub}_task-{new_task}_"
-                "space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz"
-            )
 
-            assert out["BOLD"]["path"].exists()
+        new_task = f"{task}_acq-seq"
-            assert out["BOLD"]["path"].is_file()
+        assert (
+            out["BOLD"]["path"].name == f"sub-{sub}_task-{new_task}_"
+            "space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz"
+        )
 
-            # asserts type "BOLD_confounds"
+        assert out["BOLD"]["path"].exists()
-            assert "BOLD_confounds" in out
+        assert out["BOLD"]["path"].is_file()
 
-            assert (
+        # asserts type "BOLD_confounds"
-                out["BOLD_confounds"]["path"].name
+        assert "BOLD_confounds" in out
-                == f"sub-{sub}_task-{new_task}_"
-                "desc-confounds_regressors.tsv"
-            )
 
-            assert out["BOLD_confounds"]["path"].exists()
+        assert (
-            assert out["BOLD_confounds"]["path"].is_file()
+            out["BOLD_confounds"]["path"].name == f"sub-{sub}_task-{new_task}_"
+            "desc-confounds_regressors.tsv"
+        )
 
-            # assert BOLD_mask
+        assert out["BOLD_confounds"]["path"].exists()
-            assert out["BOLD_mask"]["path"].exists()
+        assert out["BOLD_confounds"]["path"].is_file()
 
-            # asserts type "T1w"
+        # assert BOLD_mask
-            assert "T1w" in out
+        assert out["BOLD_mask"]["path"].exists()
 
-            assert (
+        # asserts type "T1w"
-                out["T1w"]["path"].name
+        assert "T1w" in out
-                == f"sub-{sub}_space-MNI152NLin2009cAsym_"
-                "desc-preproc_T1w.nii.gz"
-            )
 
-            assert out["T1w"]["path"].exists()
+        assert (
-            assert out["T1w"]["path"].is_file()
+            out["T1w"]["path"].name == f"sub-{sub}_space-MNI152NLin2009cAsym_"
+            "desc-preproc_T1w.nii.gz"
+        )
 
-            # asserts T1w_mask
+        assert out["T1w"]["path"].exists()
-            assert out["T1w_mask"]["path"].exists()
+        assert out["T1w"]["path"].is_file()
 
-            # asserts type "probseg_CSF"
+        # asserts T1w_mask
-            assert "probseg_CSF" in out
+        assert out["T1w_mask"]["path"].exists()
 
-            assert (
+        # asserts type "probseg_CSF"
-                out["probseg_CSF"]["path"].name
+        assert "probseg_CSF" in out
-                == f"sub-{sub}_space-MNI152NLin2009cAsym_label-"
-                "CSF_probseg.nii.gz"
-            )
 
-            assert out["probseg_CSF"]["path"].exists()
+        assert (
-            assert out["probseg_CSF"]["path"].is_file()
+            out["probseg_CSF"]["path"].name
+            == f"sub-{sub}_space-MNI152NLin2009cAsym_label-"
+            "CSF_probseg.nii.gz"
+        )
 
-            # asserts type "probseg_GM"
+        assert out["probseg_CSF"]["path"].exists()
-            assert "probseg_GM" in out
+        assert out["probseg_CSF"]["path"].is_file()
 
-            assert (
+        # asserts type "probseg_GM"
-                out["probseg_GM"]["path"].name
+        assert "probseg_GM" in out
-                == f"sub-{sub}_space-MNI152NLin2009cAsym_label-"
-                "GM_probseg.nii.gz"
-            )
 
-            assert out["probseg_GM"]["path"].exists()
+        assert (
-            assert out["probseg_GM"]["path"].is_file()
+            out["probseg_GM"]["path"].name
+            == f"sub-{sub}_space-MNI152NLin2009cAsym_label-"
+            "GM_probseg.nii.gz"
+        )
 
-            # asserts type "probseg_WM"
+        assert out["probseg_GM"]["path"].exists()
-            assert "probseg_WM" in out
+        assert out["probseg_GM"]["path"].is_file()
 
-            assert (
+        # asserts type "probseg_WM"
-                out["probseg_WM"]["path"].name
+        assert "probseg_WM" in out
-                == f"sub-{sub}_space-MNI152NLin2009cAsym_label-"
-                "WM_probseg.nii.gz"
-            )
 
-            assert out["probseg_WM"]["path"].exists()
+        assert (
-            assert out["probseg_WM"]["path"].is_file()
+            out["probseg_WM"]["path"].name
+            == f"sub-{sub}_space-MNI152NLin2009cAsym_label-"
+            "WM_probseg.nii.gz"
+        )
 
-            # asserts type "DWI"
+        assert out["probseg_WM"]["path"].exists()
-            assert "DWI" in out
+        assert out["probseg_WM"]["path"].is_file()
 
-            assert (
+        # asserts type "DWI"
-                out["DWI"]["path"].name == f"sub-{sub}_desc-preproc_dwi.nii.gz"
+        assert "DWI" in out
-            )
 
-            assert out["DWI"]["path"].exists()
+        assert out["DWI"]["path"].name == f"sub-{sub}_desc-preproc_dwi.nii.gz"
-            assert out["DWI"]["path"].is_file()
 
-            # asserts meta
+        assert out["DWI"]["path"].exists()
-            assert "meta" in out["BOLD"]
+        assert out["DWI"]["path"].is_file()
-            meta = out["BOLD"]["meta"]
+
-            assert "element" in meta
+        # asserts meta
-            assert "subject" in meta["element"]
+        assert "meta" in out["BOLD"]
-            assert sub == meta["element"]["subject"]
+        meta = out["BOLD"]["meta"]
+        assert "element" in meta
+        assert "subject" in meta["element"]
+        assert sub == meta["element"]["subject"]
+
+
+@pytest.mark.parametrize(
+    "types",
+    [
+        "BOLD",
+        "BOLD_confounds",
+        "T1w",
+        "probseg_CSF",
+        "probseg_GM",
+        "probseg_WM",
+        "DWI",
+        ["BOLD", "BOLD_confounds"],
+        ["T1w", "probseg_CSF"],
+        ["probseg_GM", "probseg_WM"],
+        ["DWI", "BOLD"],
+    ],
+)
+def test_DataladAOMICPIOP2_partial_data_access(
+    types: Union[str, List[str]],
+) -> None:
+    """Test DataladAOMICPIOP2 DataGrabber partial data access.
+
+    Parameters
+    ----------
+    types : str or list of str
+        The parametrized types.
+
+    """
+    dg = DataladAOMICPIOP2(types=types)
+    # Set URI to Gin
+    dg.uri = URI
+
+    with dg:
+        # Get all elements
+        all_elements = dg.get_elements()
+        # Get test element
+        test_element = all_elements[0]
+        # Get test element data
+        out = dg[test_element]
+        # Assert data type
+        if isinstance(types, list):
+            for type_ in types:
+                assert type_ in out
+        else:
+            assert types in out
+
+
+def test_DataladAOMICPIOP2_incorrect_data_type() -> None:
+    """Test DataladAOMICPIOP2 DataGrabber incorrect data type."""
+    with pytest.raises(
+        ValueError, match="`patterns` must contain all `types`"
+    ):
+        _ = DataladAOMICPIOP2(types="Vesta")
 
 
 def test_DataladAOMICPIOP2_invalid_tasks():
-    """Test whether invalid task fails."""
+    """Test DataladAOMICIDPIOP2 DataGrabber invalid tasks."""
     with pytest.raises(
         ValueError,
         match=(

junifer/datagrabber/tests/test_datagrabber_utils.py

@@ -61,7 +61,9 @@ def test_validate_patterns() -> None:
         "T1w": "{subject}/anat/{subject}_T1w.nii.gz",
     }
 
-    with pytest.raises(ValueError, match="same length"):
+    with pytest.raises(
+        ValueError, match="Length of `types` more than that of `patterns`."
+    ):
         validate_patterns(types, wrongpatterns)  # type: ignore
 
     wrongpatterns = {

junifer/datagrabber/tests/test_pattern.py

@@ -38,7 +38,9 @@ def test_PatternDataGrabber_errors(tmp_path: Path) -> None:
             replacements="subject",  # type: ignore
         )
 
-    with pytest.raises(ValueError, match=r"must have the same length"):
+    with pytest.raises(
+        ValueError, match=r"`patterns` must contain all `types`"
+    ):
         PatternDataGrabber(
             datadir="/tmp",
             types=["func", "anat"],
@@ -55,7 +57,7 @@ def test_PatternDataGrabber_errors(tmp_path: Path) -> None:
         )
 
     with pytest.raises(
-        ValueError, match=r"`patterns` must have the same length"
+        ValueError, match=r"Length of `types` more than that of `patterns`"
     ):
         PatternDataGrabber(
             datadir="/tmp",

junifer/datagrabber/utils.py

@@ -77,17 +77,17 @@ def validate_patterns(types: List[str], patterns: Dict[str, str]) -> None:
     if not isinstance(patterns, dict):
         raise_error(msg="`patterns` must be a dict.", klass=TypeError)
     # Unequal length of objects
-    if len(types) != len(patterns):
+    if len(types) > len(patterns):
         raise_error(
-            msg="`types` and `patterns` must have the same length.",
+            msg="Length of `types` more than that of `patterns`.",
             klass=ValueError,
         )
-
+    # Missing type in patterns
     if any(x not in patterns for x in types):
         raise_error(
             msg="`patterns` must contain all `types`", klass=ValueError
         )
-
+    # Wildcard check in patterns
     if any("}*" in pattern for pattern in patterns.values()):
         raise_error(
             msg="`patterns` must not contain `*` following a replacement",